Algorithm Assurance
Christian Spindler · 2020
Artificial intelligence (Al) is penetrating more and more elements of both personal lives and business processes. Especially in financial services - a data-driven business on the one hand, a regulated and privacy-concerned business on the other hand - the request for assurance, interpretability and fairness of Al algorithms rises. Risk and compliance want to know how to use Al models to manage many sorts of risk and ensure compliance in client onboarding and management. Onboarding a new client involves anti-money laundering and know-your-client processes that can be supported by Al. Machine learning is successfully employed to identify counterparty risks in both retail and commercial segments, to enable robust scoring even under the constraints of missing information. With a growing number of alternative data sources, e.g. from the Internet of Things, the performance of scoring algorithms is likely to increase further.